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PulseNet RUL Forecasting

PulseNet is an evidence-driven predictive maintenance service for NASA C-MAPSS FD001 turbofan telemetry. The repository is scoped to a defensible ML-security portfolio artifact: official data lineage, reproducible anomaly detection, API auth/RBAC, tenant traceability, audit logging, and CI smoke verification.

Current Evidence

  • Official dataset: NASA C-MAPSS FD001.
  • Archive URL: https://data.nasa.gov/docs/legacy/CMAPSSData.zip
  • Archive SHA-256: 74bef434a34db25c7bf72e668ea4cd52afe5f2cf8e44367c55a82bfd91a5a34f
  • Loader: src/pulsenet/pipeline/official_cmapss.py
  • Verification: python verify.py
  • Data lineage: docs/DATA_LINEAGE.md
  • Threat model: docs/THREAT_MODEL.md
  • Measured evidence: docs/evidence/validation_results.json
  • Metrics chart: docs/evidence/validation_metrics.svg

No generated fixture data is used in tests, CI, or smoke verification.

Security Scope

  • JWT authentication requires configured users and a configured signing secret.
  • RBAC protects prediction, training, audit, and verification endpoints.
  • X-Tenant-ID is propagated into response headers and audit metadata for traceability.
  • The audit ledger hash-chains API access events and verifies tampering.
  • Container runtime runs as a non-root user and does not bake secrets.

This is not presented as a deployed production fleet. It is a reproducible reference implementation with measured local verification.

Quick Start

python -m pip install -r requirements.txt
python verify.py

To regenerate full official-data validation metrics:

python scripts/run_validation.py

CI Gates

GitHub Actions run:

  • ruff check
  • ruff format --check
  • pytest
  • python verify.py
  • Docker build

CI must fail on lint, test, or official-data verification failure.

License

MIT

Security

See SECURITY.md for vulnerability reporting.

Contributing

See CONTRIBUTING.md for guidelines.

About

Official NASA C-MAPSS FD001 predictive-maintenance verification with data lineage, threat model, CI gates, auth/RBAC, tenant audit, and measured evidence.

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